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From a spatial monitoring and modelling perspective, models of forest growth are mature and capture well biomass increment, but do not account for forest depletions, which can result in large changes in biomass and impact the ability of forests to exchange gasses with the atmosphere.
From a practical perspective, models that are easy to generate, cheap and develop in a timely manner will be favoured over expensive and time-consuming models.
When studying hazard rates according to ER status following an exploratory perspective, models with a different shape for the hazard according to ER status were adopted.
From a research perspective, models and simulations afford the means to study aspects of sociotechnical system design and operation, including the potential impact of modifications to structural and dynamic system properties, in ways not feasible with traditional experimental approaches.
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We performed a set of experiments to evaluate the scattering model and the aerial perspective model.
To solve the previous drawbacks, Zhao [13] proposed an automatic turbidity-based aerial perspective model.
Thereby, the metal cluster [Re12μ6-CS17 CN 6]n−can be considered as a perspective model of a molecular switch.
Given the proposed aerial perspective model, we now present how to implement it on a GPU.
Gao et al. [21] presented an aerial perspective model for haze filtering based on a parameter called maximum visibility.
Following that approach, we propose a full-spectrum turbidity-based aerial perspective model that enables us to render realistic aerial perspective effects in real time.
Originally, the aerial perspective rendering equation for one viewing direction can be obtained by replacing the aerial perspective model of Eq. (1) in Eq. (7).
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